Modeling of Syrian Refugee Camps and Humanitarian Aid Warehouse Locations with Geographic Information System (GIS) and Linear Programming

Öz

Hundreds of non-governmental organizations all over the world strive to support refugees who have had to migrate from their countries due to wars and disasters and live in camps. Syria is an example in this regard. The logistics of the materials that will go to the camps from the humanitarian aid depots of the non-governmental organizations in Syria is a known and solvable humanitarian aid logistics problem. The purpose of this article is to research suitable places for non-governmental organizations (NGOs) warehouse areas. As in every humanitarian aid logistics problem, it is aimed to distribute the maximum amount of products with minimum cost while carrying out the transportation of the materials that need to be delivered to the end users and the needers from the designated warehouse locations. This study was defined and solved using Linear Programming (LP) and Geographic Information System (GIS), and cost analyzes were performed by showing a comparison between the results of each solution method.

Anahtar Kelimeler

• Facility location
• Geographic information system
• Non-governmental organizations
• Inventory

Suriye Mülteci Kamplarının ve İnsani Yardım Depo Konumlarının Coğrafi Bilgi Sistemi (CBS) ve Doğrusal Programlama ile Modellenmesi

Öz

Tüm dünyada yüzlerce sivil toplum kuruluşu, savaşlar ve afetler nedeniyle ülkelerinden göç etmek zorunda kalan ve kamplarda yaşayan mültecilere destek olmak için çaba göstermektedir. Suriye bu konuda bir örnektir. Suriye'de bulunan sivil toplum kuruluşlarının insani yardım depolarından kamplara gidecek olan malzemelerin lojistiği ise bilinen ve çözümlenebilen bir insani yardım lojistiği problemidir. Bu makalenin amacı, Sivil Toplum Kuruluşlarının (STK) depo alanları için uygun yerleri araştırmaktır. Her insani yardım lojistiği probleminde olduğu gibi belirlenen depo lokasyonlarından nihai kullanıcı ve ihtiyaç sahiplerine ulaştırılması gereken malzemelerin taşıma işlemleri gerçekleştirilirken minimum miktarda maliyet ile maksimum miktarda ürün dağıtımı amaçlanmıştır. Bu çalışma, Doğrusal Programlama (LP) ve Coğrafi Bilgi Sistemi (CBS) kullanılarak tanımlanmış, çözülmüş ve her bir çözüm yönteminin sonuçları arasında bir karşılaştırma gösterilerek maliyet analizleri yapılmıştır.

Anahtar Kelimeler

• Tesis konumu
• Coğrafi bilgi sistemi
• Sivil toplum kuruluşları
• Envanter

Kaynakça

1. 1. Farahani, R.Z., Asgari, N., Heidari, N., Hosseininia, M.,Goh, M., 2012. Covering Problems in Facility Location: A Review. Computers & Industrial Engineering, 62 (1), 368-407.
2. 2. Van Wassenhove, L.N., 2006. Humanitarian Aid Logistics: Supply Chain Management in High Gear. Journal of the Operational Research Society, 57(5), 475-489.
3. 3. Altay, N., Green, W.G., 2006. OR/MS Research in Disaster Operations Management. Eur. J. Oper. Res., 175, 475-493.
4. 4. Çelik, M., Ergun, Ö., Johnson, B., Keskinocak, P., Lorca, Á., Pekgün, P., Swann, J., 2012. Humanitarian Logistics. New Directions in Informatics, Optimization, Logistics, and Production, 18-49.
5. 5. Galindo, G., Batta, R., 2013. Review of Recent Developments in OR/MS Research in Disaster Operations Management. Eur. J. Oper. Res., 230, 201-211.
6. 6. Özdamar, L., Ertem, M.A., 2015. Models, Solutions and Enabling Technologies in Humanitarian Logistics. Eur. J. Oper. Res., 244(1), 55-65.
7. 7. Kara, B.Y., Savaş, Er, S., 2017. Humanitarian Logistics. In: Leading Developments From INFORMS Communities, 263-303.
8. 8. Besiou, M., Van Wassenhove, L.N., 2019. Humanitarian Operations: A World of Opportunity for Relevant and Impactful Research. Manufacturing & Service Operations Management 22(1), 135-145.

9. 9. Prodhon, C., Prins, C., 2014. A Survey of Recent Research on Location-Routing Problems. Eur. J. Oper. Res., 238, 1-17.
10. 10. Albareda-Sambola, M., 2015. Location-Routing and Location-Arc Routing. Springer, Cham, 399-418 .
11. 11. Drexl, M., Schneider, M., 2017. A Survey of the Standard Location-Routing Problem. Ann. Oper. Res., 259, 389-414.
12. 12. Balcik, B., Beamon, B.M., Smilowitz, K.R., 2008. Last Mile Distribution in Humanitarian Relief. Journal of Intelligent Transportation Systems, 12(2), 51-63.
13. 13. Paul, J.A., Wang, X., 2019. Robust Location-Allocation Network Design for Earthquake Preparedness. Transportation Research Part B: Methodological, 119, 139-155.
14. 14. Balcik, B., Beamon, B.M., 2008. Facility Location in Humanitarian Relief. International Journal of Logistics, 11(2), 101-121.
15. 15. Campbell, A.M., Vandenbussche, D., Hermann, W., 2008. Routing for Relief Efforts. Transportation Science, 42(2), 127-145.
16. 16. Huang, M., Smilowitz, K.R., Balcik, B., 2012. Models for Relief Routing: Equity, Efficiency and Efficacy. Transportation Research Part E: Logistics and Trans-Portation Review, 48(1), 2-18.
17. 17. Huang, M., Smilowitz, K.R., Balcik, B., 2013. A Continuous Approximation Approach for Assessment Routing in Disaster Relief. Transportation Research Part B: Methodological, 50, 20-41.
18. 18. Sheu, J.B., 2014. Post-Disaster Relief-Service Centralized Logistics Distribution with Survivor Resilience Maximization. Transportation Research Part B: Methodological, 68, 288-314.
19. 19. Oruc, B.E., Kara, B.Y., 2018. Post-Disaster Assessment Routing Problem. Transportation Research Part B: Methodological, 116, 76-102.
20. 20. Eisenhandler, O., Tzur, M., 2019. The Humanitarian Pickup and Distribution Problem. Oper. Res., 67(1), 10-32.
21. 21. Eisenhandler, O., Tzur, M., 2019. A Segment-Based Formulation and A Matheuristic for the Humanitarian Pickup and Distribution Problem. Transportation Science, 53(5), 1389-1408.
22. 22. Mills, A.F., Argon, N.T., Ziya, S., 2018. Dynamic Distribution of Patients to Medical Facilities in the Aftermath of a Disaster. Oper. Res., 66(3), 716-732.
23. 23. Yi, W., Özdamar, L., 2007. A Dynamic Logistics Coordination Model for Evacuation and Support in Disaster Response Activities. Eur J Oper Res, 179, 1177-1193.
24. 24. Balcik, B., 2017. Site Selection and Vehicle Routing for Post-Disaster Rapid Needs Assessment. Transportation Research Part E: Logistics and Transportation Review, 101, 30-58.
25. 25. Cherkesly, M., Rancourt, M.È., Smilowitz, K.R., 2019. Community Healthcare Network in Underserved Areas: Design, Mathematical Models, and Analysis. Production and Operations Management, 28(7), 1716-1734.
26. 26. Maliene, V., Grigonis, V., Palevičius, V., Griffiths, S., 2011. Geographic Information System: Old Principles with New Capabilities. Urban Design International, 16(1), 1-6.
27. 27. Li, X., Zhao, Z., Zhu, X., Wyatt, T., 2011. Covering Models and Optimization Techniques for Emergency Response Facility Location and Planning a Review. Mathematical Methods of Operations Research, 74(3), 281-310.
28. 28. Caprara, A., Toth, P., Fischetti, M., 2000. Algorithms for the Set Covering Problem. Annals of Operations Research, 98(1-4), 353-371.
29. 29. Puotinen, M., 2009. A Primer of GIS: Fundamental Geographic and Cartographic Concepts - by Francis Harvey. Geographical Research, 47(2), 219-221.
30. 30. Ye, M., Zhou, G. 2007. A Local Genetic Approach to Multi-Objective, Facility Layout Problems with Fixed Aisles. Int. J. Prod. Res., 45, 5243-5264.
31. 31. Singh, S.P., Singh, V.K., 2011. Three-Level AHP-Based Heuristic Approach for a Multi-Objective Facility Layout Problem. Int. J. Prod. Res., 49, 1105-1125.
32. 32. Teixeira, J.C., Antunes, A.P., 2008. A Hierarchical Location Model for Public Facility Planning. European Journal of Operational Research, 185(1), 92-104.
33. 33. Lovett, A., Haynes, R., Sünnenberg, G., Gale, S., 2002. Car Travel Time and Accessibility by Bus to General Practitioner Services: A Study Using Patient Registers and GIS. Social Science & Medicine, 55(1), 97-111.